Inspired by the success of image classification [1]}, [2]}, current models for visual event recognition use convolutional neural networks (CNN). Several methods have been explored to process the temporal information such as two-streams network [3]}, recurrent neural network (RNN) [4]}, and three-dimensional convolution (3D CNN) [5]}, to name a few. However, all these works ignore an important information present in video: acoustic features.
